Fix new-style implementation of Series.append() method

hpat/datatypes/common_functions.py

@@ -0,0 +1,133 @@
+# *****************************************************************************
+# Copyright (c) 2019, Intel Corporation All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+#     Redistributions of source code must retain the above copyright notice,
+#     this list of conditions and the following disclaimer.
+#
+#     Redistributions in binary form must reproduce the above copyright notice,
+#     this list of conditions and the following disclaimer in the documentation
+#     and/or other materials provided with the distribution.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
+# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
+# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
+# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
+# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
+# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
+# EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+# *****************************************************************************
+
+"""
+
+| This file contains internal common functions used in SDC implementation across different files
+
+"""
+
+import numpy
+
+from numba import types
+from numba.extending import overload
+from numba import numpy_support
+
+import hpat
+from hpat.str_arr_ext import (string_array_type, num_total_chars, append_string_array_to)
+
+
+def has_literal_value(var, value):
+    '''Used during typing to check that variable var is a Numba literal value equal to value'''
+
+    if not isinstance(var, types.Literal):
+        return False
+
+    if value is None or isinstance(value, type(bool)):
+        return var.literal_value is value
+    else:
+        return var.literal_value == value
+
+
+def has_python_value(var, value):
+    '''Used during typing to check that variable var was resolved as Python type and has specific value'''
+
+    if not isinstance(var, type(value)):
+        return False
+
+    if value is None or isinstance(value, type(bool)):
+        return var is value
+    else:
+        return var == value
+
+
+def hpat_arrays_append(A, B):
+    pass
+
+
+@overload(hpat_arrays_append)
+def hpat_arrays_append_overload(A, B):
+    '''Function for appending underlying arrays (A and B) or list/tuple of arrays B to an array A'''
+
+    if isinstance(A, types.Array):
+        if isinstance(B, types.Array):
+            def _append_single_numeric_impl(A, B):
+                return numpy.concatenate((A, B,))
+
+            return _append_single_numeric_impl
+        elif isinstance(B, (types.UniTuple, types.List)):
+            # TODO: this heavily relies on B being a homogeneous tuple/list - find a better way
+            # to resolve common dtype of heterogeneous sequence of arrays
+            np_dtypes = [numpy_support.as_dtype(A.dtype), numpy_support.as_dtype(B.dtype.dtype)]
+            np_common_dtype = numpy.find_common_type([], np_dtypes)
+            numba_common_dtype = numpy_support.from_dtype(np_common_dtype)
+
+            # TODO: refactor to use numpy.concatenate when Numba supports building a tuple at runtime
+            def _append_list_numeric_impl(A, B):
+
+                total_length = len(A) + numpy.array([len(arr) for arr in B]).sum()
+                new_data = numpy.empty(total_length, numba_common_dtype)
+
+                stop = len(A)
+                new_data[:stop] = A
+                for arr in B:
+                    start = stop
+                    stop = start + len(arr)
+                    new_data[start:stop] = arr
+                return new_data
+
+            return _append_list_numeric_impl
+
+    elif A == string_array_type:
+        if B == string_array_type:
+            def _append_single_string_array_impl(A, B):
+                total_size = len(A) + len(B)
+                total_chars = num_total_chars(A) + num_total_chars(B)
+                new_data = hpat.str_arr_ext.pre_alloc_string_array(total_size, total_chars)
+
+                pos = 0
+                pos += append_string_array_to(new_data, pos, A)
+                pos += append_string_array_to(new_data, pos, B)
+
+                return new_data
+
+            return _append_single_string_array_impl
+        elif (isinstance(B, (types.UniTuple, types.List)) and B.dtype == string_array_type):
+            def _append_list_string_array_impl(A, B):
+                array_list = [A] + list(B)
+                total_size = numpy.array([len(arr) for arr in array_list]).sum()
+                total_chars = numpy.array([num_total_chars(arr) for arr in array_list]).sum()
+
+                new_data = hpat.str_arr_ext.pre_alloc_string_array(total_size, total_chars)
+
+                pos = 0
+                pos += append_string_array_to(new_data, pos, A)
+                for arr in B:
+                    pos += append_string_array_to(new_data, pos, arr)
+
+                return new_data
+
+            return _append_list_string_array_impl

hpat/datatypes/hpat_pandas_series_functions.py

@@ -39,11 +39,11 @@
 from numba import types
 
 import hpat
+import hpat.datatypes.common_functions as common_functions
 from hpat.hiframes.pd_series_ext import SeriesType
-from hpat.str_arr_ext import StringArrayType
+from hpat.str_arr_ext import (StringArrayType, cp_str_list_to_array, num_total_chars)
 from hpat.utils import to_array
 
-
 class TypeChecker:
     """
         Validate object type and raise TypingError if the type is invalid, e.g.:
@@ -753,37 +753,92 @@ def hpat_pandas_series_isin_impl(self, values):
 
 
 @overload_method(SeriesType, 'append')
-def hpat_pandas_series_append(self, to_append):
+def hpat_pandas_series_append(self, to_append, ignore_index=False, verify_integrity=False):
     """
     Pandas Series method :meth:`pandas.Series.append` implementation.
 
     .. only:: developer
 
-       Test: python -m hpat.runtests hpat.tests.test_series.TestSeries.test_series_append1
+        Test: python -m hpat.runtests -k hpat.tests.test_series.TestSeries.test_series_append*
+
     Parameters
     -----------
-    to_append : :obj:`pandas.Series` object
-               input argument
-    ignore_index:
-                 *unsupported*
-    verify_integrity:
-                     *unsupported*
+    self: :obj:`pandas.Series`
+        input series
+    to_append : :obj:`pandas.Series` object or :obj:`list` or :obj:`set`
+        Series (or list or tuple of Series) to append with self
+    ignore_index: :obj:`bool`, default False
+        If True, do not use the index labels.
+        Supported as literal value only
+    verify_integrity: :obj:`bool`, default False
+        If True, raise Exception on creating index with duplicates.
+        *unsupported*
+
     Returns
     -------
     :obj:`pandas.Series`
-         returns :obj:`pandas.Series` object
+        returns :obj:`pandas.Series` object
+        Concatenated Series
+
     """
 
     _func_name = 'Method append().'
 
-    if not isinstance(self, SeriesType) or not isinstance(to_append, SeriesType):
+    if not isinstance(self, SeriesType):
+        raise TypingError(
+            '{} The object must be a pandas.series. Given self: {}'.format(_func_name, self))
+
+    if not (isinstance(to_append, SeriesType)
+            or (isinstance(to_append, (types.UniTuple, types.List)) and isinstance(to_append.dtype, SeriesType))):
+        raise TypingError(
+            '{} The argument must be a pandas.series or list/tuple of pandas.series. \
+            Given to_append: {}'.format(_func_name, to_append))
+
+    # currently we will always raise this in the end, i.e. if no impl was found
+    # TODO: find a way to stop compilation early and not proceed with unliteral step
+    if not (isinstance(ignore_index, types.Literal) and isinstance(ignore_index, types.Boolean)
+            or isinstance(ignore_index, types.Omitted)
+            or ignore_index is False):
+        raise TypingError(
+            '{} The ignore_index must be a literal Boolean constant. Given: {}'.format(_func_name, ignore_index))
+
+    if not (verify_integrity is False or isinstance(verify_integrity, types.Omitted)):
         raise TypingError(
-            '{} The object must be a pandas.series. Given self: {}, to_append: {}'.format(_func_name, self, to_append))
+            '{} Unsupported parameters. Given verify_integrity: {}'.format(_func_name, verify_integrity))
+
+    # ignore_index value has to be known at compile time to select between implementations with different signatures
+    ignore_index_is_false = (common_functions.has_literal_value(ignore_index, False)
+                             or common_functions.has_python_value(ignore_index, False)
+                             or isinstance(ignore_index, types.Omitted))
+    to_append_is_series = isinstance(to_append, SeriesType)
+
+    if ignore_index_is_false:
+        def hpat_pandas_series_append_impl(self, to_append, ignore_index=False, verify_integrity=False):
+            if to_append_is_series == True:  # noqa
+                new_data = common_functions.hpat_arrays_append(self._data, to_append._data)
+                new_index = common_functions.hpat_arrays_append(self.index, to_append.index)
+            else:
+                data_arrays_to_append = [series._data for series in to_append]
+                index_arrays_to_append = [series.index for series in to_append]
+                new_data = common_functions.hpat_arrays_append(self._data, data_arrays_to_append)
+                new_index = common_functions.hpat_arrays_append(self.index, index_arrays_to_append)
+
+            return pandas.Series(new_data, new_index)
+
+        return hpat_pandas_series_append_impl
+
+    else:
+        def hpat_pandas_series_append_ignore_index_impl(self, to_append, ignore_index=False, verify_integrity=False):
+
+            if to_append_is_series == True:  # noqa
+                new_data = common_functions.hpat_arrays_append(self._data, to_append._data)
+            else:
+                arrays_to_append = [series._data for series in to_append]
+                new_data = common_functions.hpat_arrays_append(self._data, arrays_to_append)
 
-    def hpat_pandas_series_append_impl(self, to_append):
-        return pandas.Series(self._data + to_append._data)
+            return pandas.Series(new_data, None)
 
-    return hpat_pandas_series_append_impl
+        return hpat_pandas_series_append_ignore_index_impl
 
 
 @overload_method(SeriesType, 'copy')

hpat/hiframes/api.py

@@ -36,7 +36,7 @@
 
 import numba
 from numba import ir, ir_utils
-from numba import types, cgutils
+from numba import numpy_support, types, cgutils
 from numba.ir_utils import require, mk_unique_var
 import numba.array_analysis
 from numba.typing import signature
@@ -56,7 +56,12 @@
 from hpat.utils import _numba_to_c_type_map, unliteral_all
 from hpat.str_ext import string_type, list_string_array_type
 from hpat.set_ext import build_set
-from hpat.str_arr_ext import (StringArrayType, string_array_type, is_str_arr_typ)
+from hpat.str_arr_ext import (
+    StringArrayType,
+    string_array_type,
+    is_str_arr_typ,
+    num_total_chars,
+    append_string_array_to)
 from hpat.hiframes.pd_timestamp_ext import (pandas_timestamp_type, datetime_date_type, set_df_datetime_date_lower)
 from hpat.hiframes.pd_series_ext import (
     SeriesType,

hpat/hiframes/pd_series_ext.py

@@ -1288,7 +1288,7 @@ def hpat_pandas_series_ctor_impl(data=None, index=None, dtype=None, name=None, c
 
         '''' use binop here as otherwise Numba's dead branch pruning doesn't work
         TODO: replace with 'if not is_index_none' when resolved '''
-        if is_index_none == False:
+        if is_index_none == False:  # noqa
             fix_index = hpat.hiframes.api.fix_df_array(index)
         else:
             fix_index = index

hpat/str_arr_ext.py

@@ -1419,3 +1419,17 @@ def lower_glob(context, builder, sig, args):
     # context.nrt.decref(builder, ty, ret)
 
     return impl_ret_new_ref(context, builder, typ, ret)
+
+
+@numba.njit(no_cpython_wrapper=True)
+def append_string_array_to(result, pos, A):
+    # precondition: result is allocated with the size enough to contain A
+    i, j = 0, pos
+    for str in A:
+        result[j] = str
+        if str_arr_is_na(A, i):
+            hpat.str_arr_ext.str_arr_set_na(result, j)
+        i += 1
+        j += 1
+
+    return i